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Trajectory Tracking Control for Autonomous Driving Vehicle with Obstacle Avoidance: Modeling, Simulation, and Performance Analysis
ISSN: 2574-0741, e-ISSN: 2574-075X
Published November 16, 2019 by SAE International in United States
Citation: Zhan, H., Shi, S., Lin, C., and Huang, Q., "Trajectory Tracking Control for Autonomous Driving Vehicle with Obstacle Avoidance: Modeling, Simulation, and Performance Analysis," SAE Intl. J CAV 3(1):5-17, 2020, https://doi.org/10.4271/12-03-01-0001.
The external driving environment of an autonomous driving vehicle is complex and changeable. In this article, the trajectory tracking control with obstacle avoidance based on model predictive control was presented. Specifically, double-level control scheme by controlling the front steering angle was used in our research, and the double level is composed of the high level of model predictive controller for local trajectory planning and low level of model predictive controller for trajectory tracking. At high level, the local trajectory planner based on the point-mass model was designed. Then, at low level, the linear time-varying vehicle dynamics model was presented, and the trajectory tracking controller was proposed considering control variable, control increment, and output constraint. Finally, the trajectory tracking performance was tested in co-simulation environment with CarSim and Simulink, and the tracking errors were analyzed. Compared with the controller without a high level for local trajectory planning, this article indicates that the trajectory tracking controller has rather effective and efficient trajectory tracking performance during all conventional cases, which shows strong robustness to vehicle speed.